Rapid classification of surface reflectance from image velocities

Katja Doerschner, Dan Kersten, Paul Schrater

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We propose a method for rapidly classifying surface reflectance directly from the output of spatio-temporal filters applied to an image sequence of rotating objects. Using image data from only a single frame, we compute histograms of image velocities and classify these as being generated by a specular or a diffusely reflecting object. Exploiting characteristics of material-specific image velocities we show that our classification approach can predict the reflectance of novel 3D objects, as well as human perception.

Original languageEnglish (US)
Title of host publicationComputer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings
Pages856-864
Number of pages9
DOIs
StatePublished - 2009
Event13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 - Munster, Germany
Duration: Sep 2 2009Sep 4 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5702 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009
Country/TerritoryGermany
CityMunster
Period9/2/099/4/09

Bibliographical note

Funding Information:
KD has been supported by an EC FP7 Marie Curie IRG-239494. Further funding was provided by an NIH RO1 EY015261.

Keywords

  • Material perception
  • Rapid surface reflectance classification
  • Spatio-temporal filtering
  • Specular flow
  • Velocity histogram

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